What is LangChain? 

After watching a ton of courses on coursera developed by prestigious universities, and tech companies like google, meta, etc., I found IBM' courses are the best: comprehensive, clear and concise! Thank you

I appreciate presenters and mentors who make concepts easy to understand, as I am not a native English speaker.

Just want to thank the wonderful presenters for this excellent series and IBM for its commitment, innovation, and broad contribution to education in this field.

Best description of LangChain I have watched

Pure gold! Thanks a lot for this. Best regards from Nairobi, Kenya

Great topic and great presentation of it -- a good breakdown of what it is and the use-cases it tries to fulfill. I like how you filled in some of the text instead of writing it out -- saves a lot of time. Thanks.

This was super useful and easy to understand, thank you so much for posting!

great work for this complicated frame work!

martin KEEN(nominative determinism at work?) is my all-time fav IBM presenter! THis one no exception Great, clear expo of LangChain..

Thanks for sharing your knowladge with us. Thanks from Brazil.

A complex topic explained clearly.

Way to break down the chain. Well done.

Great video! I just published a chat bot for home brewers, but it’s a bit basic so a friend of mine recommended using langchain to have it provide better responses and take meaningful actions. This was really helpful for me to get started, thank you!

Thank you, Great tutorial, and easy to understand manner. We would like to ask you to explain about Lang chain concepts like indexes and chains. thank u again.

As always informative and entertaining at the same time. Would be great if you could show us some demo applications as well as some high level sample integration code or component. Thanks.

Thank you very much for this introduction! I found it really useful and helps me navigate all the information and new programs around AI. Would you be able to provide few examples on what can we built on langchain ?

Great explaination. Thank you

LangChain exists a long time and its community is huge. Nice to finally get an intro from IBM about that long existing technology and community product.

Very well explained ! Thx

Can we expand the capacity of input prompt using langchain if yes can you suggest any methods??

very helpful, thanks!

What a great explainer video.

Best explanation.

In the same program can we query one LLM (Like Llama2) , get response & use that response in a chain and pass that to another LLM (like google gemini)... All the in same program?

thank you

How does langchain stack against llama index? Which is most preferred?

wao great presentation

Can you use this tools to create a chatbot for internal databases and taking care of the data privacy? For example, I have my documents with private information and I want to use Langchain to ask question about it... Can I create it with langchain without exposing my data?

brilliant!

Ibm explaining langchain. I guess langchain is getting production ready. During the start langchain was a bit rough.

Most people use langchain to extend memory on LLMs, do you have an alternative for that?

Best explanation. Please can IBM provide end to end AI courses that can make us market ready for AI job or creating AI start up. So many noises out there

- [00:00] 🛠 LangChain Overview - LangChain is an open-source framework for developing applications utilizing large language models (LLMs). - Components of LangChain include abstractions, LLM modules, prompts, and chains, streamlining the programming of LLM applications. - [01:26] 🔄 Abstractions in LangChain - Abstractions in LangChain simplify complex NLP tasks by representing common steps and concepts necessary to work with language models. - These abstractions can be chained together to create applications, minimizing the amount of code required. - [02:22] 🔗 Components of LangChain - LangChain comprises LLM modules, prompts, and chains, enabling developers to integrate different models and execute sequential functions to achieve desired tasks. - Components like prompts formalize the composition of instructions given to LLMs, facilitating the development process. - [03:47] 📊 Data Handling in LangChain - LangChain supports various data handling mechanisms, including document loaders and text splitters, enabling access to external data sources and efficient text processing. - Vector databases and memory utilities enhance data retrieval and management within LangChain applications. - [06:09] 🤖 LangChain Use Cases - LangChain facilitates diverse applications such as chatbots, summarization, question answering, data augmentation, and virtual agents. - Integration with existing workflows and robotic process automation (RPA) enhances the functionality of LangChain.

cool video)

Am I the only one who wonders how this presentation actually works? Is he writing on a mirror? If he wrote on glass while standing behind it, it would be in reverse for us... How does some of the words autocomplete? How does it glow? Is it magic?

Just to clarify, LangChain ~= JSON but for LLMs?

Does he write inversely on the board?

Hold up... Am I watching a video on LLMs from the same guy that I've learned about home brewing from?!?!?

I was a little scared that this would be a blockchain thing.

LanguageModelChaingang ;)

Um.. why is brulosophy guy on IBM's channel explaining langchain??

👏👏

That's it folks.. It's happening.. I'm scared about what this technology can do

So this is what Ole is upto after leaving Man Utd

Is he right or left handed

honestly, I dont really like lang chain, I'd rather write the code myself to do this because its pretty trivial. seems more like something for non-techinical people who arent in tech

4000 laoff today. are you affected.

why?why?why?Why IBM know everything but lose AI age?

Everything, what could be done with langchain, better to be done without langchain. Langchain is everything bad from huggingface, without anything good, except false promise to make AI go brrrr with few lines of code. Okay, it will go brrrrr. But slowly. And when you'll need something at least a bit uncommon, you'll find, that everything is obfuscated behind several levels of unnecessary abstractions. And you'll need to rewrite everything.

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Way to break down the chain. Well done.